Gain-of-function and loss-of-function studies are commonly used to examine gene function in vivo, particularly in attempts to model human disease in animals. Developing animal models of disease is key to the process of elucidating neuropsychiatric disease pathophysiology, in turn leading to drug discovery and translation to patient populations. However, these studies typically involve generating separate lines of transgenic mice that over- or under-express the gene of interest, a process that can take several years. Increasing the speed of this screening process is of utmost importance for development of new neuropsychiatric medications based on novel genetic targets.
It is often not possible to predict how changes in candidate gene expression patterns will affect behavior. This is clearly demonstrated by the example of the serotonin transporter (SERT). SERT knockout mice, which have increased levels of serotonin throughout life due to constitutive absence of SERT, demonstrate increased depression-related behavior (1). In contrast, SERT overexpression yields a low-anxiety phenotype (2). These results were not expected since blocking SERT in adulthood with serotonin-reuptake inhibitors leads to decreased depression and anxiety. This example clearly demonstrates the need for empirical determination of effects of changes in gene expression when developing clinically-relevant animal models.